{
 "cells": [
  {
   "cell_type": "code",
   "id": "initial_id",
   "metadata": {
    "collapsed": true,
    "ExecuteTime": {
     "end_time": "2025-03-04T10:56:05.755549Z",
     "start_time": "2025-03-04T10:56:04.442774Z"
    }
   },
   "source": [
    "import numpy as np\n",
    "from matplotlib import pyplot as plt\n",
    "\n",
    "us_file_path = \"./youtube_video_data/US_video_data_numbers.csv\"\n",
    "uk_file_path = \"./youtube_video_data/GB_video_data_numbers.csv\"\n",
    "# t1 = np.loadtxt(us_file_path,delimiter=\",\",dtype=\"int\",unpack=True)\n",
    "t_us = np.loadtxt(us_file_path, delimiter=\",\", dtype=\"int\")\n",
    "print(t_us.shape)\n",
    "# 取评论的数据\n",
    "t_us_comments = t_us[:, -1]\n",
    "# 怎么知道分多少，打印最大和最小值\n",
    "print(t_us_comments.max(), t_us_comments.min())\n",
    "d = 10000\n",
    "bin_nums = (t_us_comments.max() - t_us_comments.min()) // d\n",
    "# 绘图\n",
    "plt.figure(figsize=(20, 8), dpi=80)\n",
    "plt.hist(t_us_comments, bin_nums)\n",
    "plt.show()"
   ],
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(1688, 4)\n",
      "582624 0\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 1600x640 with 1 Axes>"
      ],
      "image/png": "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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "execution_count": 1
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-03-04T11:02:55.924970Z",
     "start_time": "2025-03-04T11:02:55.578979Z"
    }
   },
   "cell_type": "code",
   "source": [
    "#选择比 5000 小的数据\n",
    "t_us_comments = t_us_comments[t_us_comments <= 5000]  # 选择评论数小于等于5000的数据\n",
    "print(t_us_comments.shape)\n",
    "print(t_us_comments.max(), t_us_comments.min()) \n",
    "d = 50\n",
    "bin_nums = (t_us_comments.max() - t_us_comments.min()) // d\n",
    "#绘图\n",
    "plt.figure(figsize=(20, 8), dpi=80)\n",
    "plt.hist(t_us_comments, bin_nums)\n",
    "plt.show()"
   ],
   "id": "a507d9d8127d5878",
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(1373,)\n",
      "4995 0\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 1600x640 with 1 Axes>"
      ],
      "image/png": "iVBORw0KGgoAAAANSUhEUgAABQQAAAIOCAYAAADuogBzAAAAOnRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjEwLjEsIGh0dHBzOi8vbWF0cGxvdGxpYi5vcmcvc2/+5QAAAAlwSFlzAAAMTgAADE4Bf3eMIwAAI0pJREFUeJzt3W1slXf9+PFPSYE5gS0yubOUutDNm92y1eCWgcuiLvJg0w01c2yoS2GJIaZ7QB8Y9YFBSJYmc0bZfFA1TRZRcE/qdHNxMKKbEEXdNKwgXSm2q0ONdnEK7vxyXYb+5Q9i6d1p+3m9khPOua7TXl9KLw598/2eq6ZSqVQCAAAAAEhhRrUHAAAAAABMHEEQAAAAABIRBAEAAAAgEUEQAAAAABIRBAEAAAAgEUEQAAAAABKpjUlo9uzZ8da3vrXawwAAAACAKemPf/xj/OMf/5g6QbCIgb29vdUeBgAAAABMSXV1daNbMrxp06ZoaGiImpqaOHDgwND2ojJ+5jOficbGxrjyyivj7rvvHtrX1dUVN9xwQ1x22WXR1NQUL7744mh/HwAAAADAKA0rCN55552xd+/eWLZs2WnbW1tby0j40ksvxW9+85t48MEHh/Zt2LAhmpuby32bN2+O9evXj3asAAAAAMAo1VQqlcpwn1zMEnz88cfjmmuuiddeey0WL15cLu2dN2/eac8bGBiI5cuXx5/+9Keora2N4hDFc4uoWGwfzpRGS4YBAAAAYGTO1ddGfJXhw4cPx1ve8pbYsmVLXH/99XHTTTfF008/Xe47evRoGQCLGFgoZhHW19dHT0/PSA8HAAAAAIyBEQfBkydPxssvvxzvete7Yv/+/fGVr3wlPvaxj8Urr7xy3p+rra2trJanboODgyMdFgAAAAAwHkGwmPE3Y8aM+MQnPlE+vvbaa+Ptb397+V6CS5cujb6+vjIaFoolw8XswOJjzqalpaWcwnjqNmfOnJEOCwAAAAAYjyB4ySWXxC233BI/+tGPysdHjhwpb+985ztjwYIFsWLFiujo6Cj37dy5s5z5N5z3DwQAAAAAqnxRkeKKwZ2dndHf3x/z58+PuXPnxqFDh+L3v/99fPrTn45XX321nC34+c9/Pu64447yYw4ePFheWfj48ePlRUfa29vjyiuvHNagXFQEAAAAAEbuXH3tvK4yPFEEQQAAAACYZFcZBgAAAACmHkEQAAAAABIRBAEAAAAgEUEQAAAAABIRBAEAAAAgEUEQAAAAABIRBAEAAAAgEUEQAAAAABIRBAEAAAAgEUEQAAAAABIRBAEAAAAgEUEQAAAAABIRBAEAAAAgkdpqDyCjhtbO83p+99Y14zYWAAAAAHIxQxAAAAAAEhEEAQAAACARQRAAAAAAEhEEAQAAACARQRAAAAAAEhEEAQAAACARQRAAAAAAEhEEAQAAACARQRAAAAAAEhEEAQAAACARQRAAAAAAEhEEAQAAACARQRAAAAAAEhEEAQAAACARQRAAAAAAEhEEAQAAACARQRAAAAAAEhEEAQAAACARQRAAAAAAEhEEAQAAACARQRAAAAAAEhEEAQAAACARQRAAAAAAEhEEAQAAACARQRAAAAAAEhEEAQAAACARQRAAAAAAEhEEAQAAACARQRAAAAAAEhEEAQAAACARQRAAAAAAEhEEAQAAACARQRAAAAAAEhEEAQAAACARQRAAAAAAEhEEAQAAACARQRAAAAAAEhEEAQAAACCRYQXBTZs2RUNDQ9TU1MSBAwfO2N/e3l7ue/zxx4e2DQwMxK233hqNjY1xxRVXxJ49e8Z25AAAAADA+ATBO++8M/bu3RvLli07Y193d3d84xvfiJUrV562vbW1tdzW1dVVBsO77rorTpw4cf4jBAAAAAAmNgiuWrUq6urqztj+xhtvxH333RcPP/xwzJ49+7R9O3bsiI0bN5b3m5qaYsmSJbF79+6xGjcAAAAAMNHvIdjW1hY33nhjXHfddadtP378eDkbcNGiRUPbiiXHPT09ozkcAAAAADBKtSP9wBdeeCF27tw5Ju8NWITF4nbK4ODgqD8nAAAAADCGMwSfffbZ8v0Di4uGFLP/nnvuuWhubo6vf/3rMX/+/KitrY3+/v6h5xfPra+vP+vnamlpid7e3qHbnDlzRjosAAAAAGA8guD9998ffX19ZegrbsUFRB599NFye2Ht2rWxffv28v6+ffvi2LFjsXr16pEeDgAAAACYqCC4YcOG8qIixey9D37wg7F8+fL/+THbtm2Ln/70p+UMwvXr10dHR0fMnDlzLMYMAAAAAIznewg+8sgj//M5zzzzzGmPFy5cGE8++eRIxwUAAAAATLarDAMAAAAAU4sgCAAAAACJCIIAAAAAkIggCAAAAACJCIIAAAAAkIggCAAAAACJCIIAAAAAkIggCAAAAACJCIIAAAAAkIggCAAAAACJCIIAAAAAkIggCAAAAACJCIIAAAAAkIggCAAAAACJCIIAAAAAkIggCAAAAACJCIIAAAAAkIggCAAAAACJCIIAAAAAkIggCAAAAACJCIIAAAAAkIggCAAAAACJCIIAAAAAkIggCAAAAACJCIIAAAAAkIggCAAAAACJCIIAAAAAkIggCAAAAACJCIIAAAAAkIggCAAAAACJCIIAAAAAkIggCAAAAACJCIIAAAAAkIggCAAAAACJCIIAAAAAkIggCAAAAACJCIIAAAAAkIggCAAAAACJCIIAAAAAkIggCAAAAACJCIIAAAAAkIggCAAAAACJCIIAAAAAkIggCAAAAACJCIIAAAAAkIggCAAAAACJCIIAAAAAkIggCAAAAACJCIIAAAAAkIggCAAAAACJCIIAAAAAkIggCAAAAACJDCsIbtq0KRoaGqKmpiYOHDhQbnv99dfj9ttvj8suuyyuvvrqeP/73x+HDh0a+piBgYG49dZbo7GxMa644orYs2fP+P0uAAAAAICxC4J33nln7N27N5YtW3ba9ubm5jh48GD86le/ittuuy3uu+++oX2tra2xcuXK6Orqivb29rjrrrvixIkTwxsVAAAAAFC9ILhq1aqoq6s7bdsFF1wQH/rQh8pZg4Ui/nV3dw/t37FjR2zcuLG839TUFEuWLIndu3eP7egBAAAAgOq8h+BDDz1UzhIsHD9+vJwNuGjRoqH9xZLjnp6esTocAAAAADACtTEGtmzZUr5/4NNPPz2ij29raytvpwwODo7FsAAAAACAsZ4h+OCDD8auXbviiSeeiAsvvLDcNn/+/KitrY3+/v6h5xXLievr68/6OVpaWqK3t3foNmfOnNEOCwAAAAAY6yBYzOp77LHH4qmnnoqLL774tH1r166N7du3l/f37dsXx44di9WrV4/mcAAAAADARCwZ3rBhQ3R2dpYz/j74wQ/G3Llz45lnnokHHnggLr300rj55pvL582ePTuef/758v62bdti3bp10djYGLNmzYqOjo6YOXPmaMcLAAAAAIx3EHzkkUfOur1SqfzXj1m4cGE8+eSTIx8ZAAAAADB5rzIMAAAAAEx+giAAAAAAJCIIAgAAAEAigiAAAAAAJCIIAgAAAEAigiAAAAAAJCIIAgAAAEAigiAAAAAAJCIIAgAAAEAigiAAAAAAJCIIAgAAAEAigiAAAAAAJCIIAgAAAEAigiAAAAAAJCIIAgAAAEAigiAAAAAAJCIIAgAAAEAigiAAAAAAJCIIAgAAAEAigiAAAAAAJCIIAgAAAEAigiAAAAAAJCIIAgAAAEAigiAAAAAAJCIIAgAAAEAigiAAAAAAJCIIAgAAAEAigiAAAAAAJCIIAgAAAEAigiAAAAAAJCIIAgAAAEAigiAAAAAAJCIIAgAAAEAigiAAAAAAJCIIAgAAAEAigiAAAAAAJCIIAgAAAEAigiAAAAAAJCIIAgAAAEAigiAAAAAAJCIIAgAAAEAigiAAAAAAJCIIAgAAAEAigiAAAAAAJCIIAgAAAEAigiAAAAAAJCIIAgAAAEAigiAAAAAAJCIIAgAAAEAigiAAAAAAJCIIAgAAAEAigiAAAAAAJDKsILhp06ZoaGiImpqaOHDgwND2rq6uuOGGG+Kyyy6LpqamePHFF4e1DwAAAACYxEHwzjvvjL1798ayZctO275hw4Zobm6Ol156KTZv3hzr168f1j4AAAAAYBIHwVWrVkVdXd1p2wYGBmL//v1x9913l4/vuOOOOHr0aBw6dOic+wAAAACAKfgegkXgW7x4cdTW1paPi+XE9fX10dPTc859Z9PW1lYGx1O3wcHBkQ4LAAAAAJjsFxVpaWmJ3t7eoducOXOqPSQAAAAAmJb+PYVvBJYuXRp9fX1x8uTJciZgpVIpZwAWMwHnzZv3X/cBAAAAAFNwhuCCBQtixYoV0dHRUT7euXNnudx3+fLl59wHAAAAAFRPTaWYvvc/FFcM7uzsjP7+/pg/f37MnTu3vEDIwYMHy6sHHz9+vJwV2N7eHldeeWX5Mefa978U8bBYOjxdNbR2ntfzu7euGbexAAAAADD9nKuvDSsITjRB8HSCIAAAAABj1dcmxUVFAAAAAICJIQgCAAAAQCKCIAAAAAAkIggCAAAAQCKCIAAAAAAkIggCAAAAQCKCIAAAAAAkIggCAAAAQCKCIAAAAAAkIggCAAAAQCKCIAAAAAAkIggCAAAAQCKCIAAAAAAkIggCAAAAQCKCIAAAAAAkIggCAAAAQCKCIAAAAAAkIggCAAAAQCKCIAAAAAAkIggCAAAAQCKCIAAAAAAkIggCAAAAQCKCIAAAAAAkIggCAAAAQCKCIAAAAAAkIggCAAAAQCKCIAAAAAAkIggCAAAAQCKCIAAAAAAkIggCAAAAQCKCIAAAAAAkIggCAAAAQCKCIAAAAAAkIggCAAAAQCKCIAAAAAAkIggCAAAAQCKCIAAAAAAkIggCAAAAQCKCIAAAAAAkIggCAAAAQCKCIAAAAAAkIggCAAAAQCKCIAAAAAAkIggCAAAAQCKCIAAAAAAkIggCAAAAQCKCIAAAAAAkIggCAAAAQCKCIAAAAAAkIggCAAAAQCKCIAAAAAAkIggCAAAAQCJjEgR/8IMfxIoVK+Kaa66JK664Ir71rW+V2wcGBuLWW2+NxsbGcvuePXvG4nAAAAAAwAjVxihVKpW4++6745lnnomrrroquru74x3veEd85CMfidbW1li5cmX88Ic/jH379sWHP/zhOHLkSMycOXO0hwUAAAAAqjVDsKamJv7yl7+U9//617/G/PnzY/bs2bFjx47YuHFjub2pqSmWLFkSu3fvHotDAgAAAADVmCFYxMDvfOc75YzAN7/5zfHnP/85du3aFX/729/ixIkTsWjRoqHnNjQ0RE9Pzxmfo62trbydMjg4ONphAQAAAADjMUPw5MmT8aUvfamMgC+//HI8/fTTsW7dunL7cLW0tERvb+/Qbc6cOaMdFgAAAAAwHkHwwIED8Yc//CFWrVo1tDS4rq4ufv3rX0dtbW309/cPPbd4f8H6+vrRHhIAAAAAqFYQXLp0afT19cXvfve78vGhQ4fi8OHDcfnll8fatWtj+/bt5fbioiLHjh2L1atXj/aQAAAAAEC13kNw4cKF8eijj8ZHP/rRmDFjRrzxxhvx1a9+tZwJuG3btnL5cGNjY8yaNSs6OjpcYRgAAAAAqqimUqlUYpIplhwX7yU4XTW0dp7X87u3rhm3sQAAAAAw/Zyrr416yTAAAAAAMHUIggAAAACQiCAIAAAAAIkIggAAAACQyKivMszkugiJC5AAAAAAcC5mCAIAAABAIoIgAAAAACQiCAIAAABAIoIgAAAAACQiCAIAAABAIoIgAAAAACQiCAIAAABAIoIgAAAAACQiCAIAAABAIoIgAAAAACQiCAIAAABAIoIgAAAAACQiCAIAAABAIoIgAAAAACQiCAIAAABAIoIgAAAAACQiCAIAAABAIoIgAAAAACQiCAIAAABAIoIgAAAAACQiCAIAAABAIoIgAAAAACQiCAIAAABAIoIgAAAAACQiCAIAAABAIoIgAAAAACQiCAIAAABAIoIgAAAAACQiCAIAAABAIoIgAAAAACQiCAIAAABAIoIgAAAAACQiCAIAAABAIoIgAAAAACQiCAIAAABAIoIgAAAAACQiCAIAAABAIoIgAAAAACQiCAIAAABAIoIgAAAAACQiCAIAAABAIoIgAAAAACQiCAIAAABAIoIgAAAAACQiCAIAAABAIoIgAAAAACQiCAIAAABAIrVj8Un+8Y9/xAMPPBA/+tGP4oILLoirr746Ojo6oqurK+6999549dVX46KLLopvfvOb8e53v3ssDsl/0dDaOezndm9dM65jAQAAAGCaBsHW1taoqamJl156qfy1v7+/3L5hw4Zobm6O9evXx/e+973y13379o3FIQEAAACAEaipVCqVGIXXXnstFi9eHL29vTFv3ryh7QMDA7F8+fL405/+FLW1tVEcpnje3r17y+3nUldXV36+6ep8ZvGNJzMEAQAAAKanc/W1Ub+H4OHDh+Mtb3lLbNmyJa6//vq46aab4umnn46jR4+WAbCIgYVi5mB9fX309PSc8Tna2trKQZ66DQ4OjnZYAAAAAMB4BMGTJ0/Gyy+/HO9617ti//798ZWvfCU+9rGPlduHq6WlpSyWp25z5swZ7bAAAAAAgPEIgsWsvxkzZsQnPvGJ8vG1114bb3/728tI2NfXNxQGiyXDxezA4vkAAAAAwBQNgpdccknccsst5RWGC0eOHClvN954Y6xYsaK82nBh586d5XLg//X+gQAAAADAJL/K8Pbt2+PTn/50bN68uZwt+Mgjj8Tb3va28tfiysLF+wsWFxxpb28fi8MBAAAAANUMgpdeemn85Cc/OWP75ZdfHj/72c/G4hAAAAAAwGRYMgwAAAAATB2CIAAAAAAkIggCAAAAQCKCIAAAAAAkIggCAAAAQCKCIAAAAAAkIggCAAAAQCKCIAAAAAAkIggCAAAAQCKCIAAAAAAkIggCAAAAQCKCIAAAAAAkIggCAAAAQCKCIAAAAAAkIggCAAAAQCKCIAAAAAAkIggCAAAAQCKCIAAAAAAkIggCAAAAQCKCIAAAAAAkIggCAAAAQCKCIAAAAAAkUlvtAVA9Da2d5/X87q1rxm0sAAAAAEwMMwQBAAAAIBFBEAAAAAASEQQBAAAAIBFBEAAAAAASEQQBAAAAIBFBEAAAAAASEQQBAAAAIBFBEAAAAAASEQQBAAAAIBFBEAAAAAASEQQBAAAAIBFBEAAAAAASEQQBAAAAIBFBEAAAAAASEQQBAAAAIBFBEAAAAAASEQQBAAAAIBFBEAAAAAASEQQBAAAAIBFBEAAAAAASEQQBAAAAIBFBEAAAAAASEQQBAAAAIBFBEAAAAAASEQQBAAAAIBFBEAAAAAASEQQBAAAAIBFBEAAAAAASEQQBAAAAIJHasfxk7e3t8alPfSq+//3vx+233x4DAwNxzz33xOHDh2P27Nnxta99LVatWjWWh2SSamjtPK/nd29dM25jAQAAAGAcZgh2d3fHN77xjVi5cuXQttbW1vJxV1dXGQvvuuuuOHHixFgdEgAAAACoRhB844034r777ouHH364nAl4yo4dO2Ljxo3l/aampliyZEns3r17LA4JAAAAAFQrCLa1tcWNN94Y11133dC248ePl7MBFy1aNLStoaEhenp6zvrxdXV1Q7fBwcGxGBYAAAAAMNbvIfjCCy/Ezp07Y8+ePSP+HC0tLeXtlCIKAgAAAACTcIbgs88+W75/YGNjYzkD8Lnnnovm5uZyuXBtbW309/cPPbd4Xn19/WgPCQAAAABUKwjef//90dfXV8a+4lZcROTRRx8tt69duza2b99ePm/fvn1x7NixWL169WgPCQAAAABUa8nwuWzbti3WrVtXzh6cNWtWdHR0xMyZM8fzkAAAAADARAbBZ555Zuj+woUL48knnxzrQwAAAAAAk3GGIFRbQ2vneT2/e+uacRsLAAAAwLR4D0EAAAAAYOoQBAEAAAAgEUuGmZJLewEAAAAYGTMEAQAAACARQRAAAAAAEhEEAQAAACAR7yHIsHmfv9F9Pbq3rhm3sQAAAAAMlxmCAAAAAJCIIAgAAAAAiVgyDP/BsmgAAABgujNDEAAAAAASEQQBAAAAIBFBEAAAAAASEQQBAAAAIBFBEAAAAAAScZVhmIRXMO7eumZcxwIAAADkZYYgAAAAACQiCAIAAABAIoIgAAAAACQiCAIAAABAIoIgAAAAACQiCAIAAABAIoIgAAAAACQiCAIAAABAIoIgAAAAACQiCAIAAABAIoIgAAAAACQiCAIAAABAIoIgAAAAACQiCAIAAABAIoIgAAAAACQiCAIAAABAIoIgAAAAACQiCAIAAABAIoIgAAAAACQiCAIAAABAIoIgAAAAACQiCAIAAABAIoIgAAAAACRSW+0BAKPT0Np5Xs/v3rpm3MYy3b9+vnYAAABMB2YIAgAAAEAigiAAAAAAJCIIAgAAAEAigiAAAAAAJCIIAgAAAEAigiAAAAAAJCIIAgAAAEAigiAAAAAAJFJb7QEAk1dDa+ewn9u9dc24jgUAAAAYG2YIAgAAAEAigiAAAAAAJDLqJcOvv/56fPzjH4/f/va38aY3vSkWLFgQX//612P58uUxMDAQ99xzTxw+fDhmz54dX/va12LVqlVjM3KAMVjqDAAAANmMyQzB5ubmOHjwYPzqV7+K2267Le67775ye2tra6xcuTK6urqivb097rrrrjhx4sRYHBIAAAAAqEYQvOCCC+JDH/pQ1NTUlI+LANjd3V3e37FjR2zcuLG839TUFEuWLIndu3eP9pAAAAAAwGS5yvBDDz1UzhI8fvx4ORtw0aJFQ/saGhqip6fnjI9pa2srb6cMDg6O9bAAJnwpsisvAwAAMO0vKrJly5Y4dOhQfPnLXz6vj2tpaYne3t6h25w5c8ZyWAAAAADAWAfBBx98MHbt2hVPPPFEXHjhhTF//vyora2N/v7+oecUS4nr6+vH6pAAAAAAQDWWDBfLfR977LH48Y9/HBdffPHQ9rVr18b27dvji1/8Yuzbty+OHTsWq1evHotDAom4ajAAAABMoiBYLPF94IEH4tJLL42bb7653DZ79ux4/vnnY9u2bbFu3bpobGyMWbNmRUdHR8ycOXMsxg0AAAAAVCMI1tXVRaVSOeu+hQsXxpNPPjnaQwAAAAAAk/Uqw8DkXiJr+S0AAADkNqZXGQYAAAAAJjdBEAAAAAASsWQYYAo6n6Xf3VvXTPtxAAAAMHxmCAIAAABAIoIgAAAAACRiyTAAQ1yF+kyWRQMAANONGYIAAAAAkIggCAAAAACJCIIAAAAAkIggCAAAAACJCIIAAAAAkIggCAAAAACJ1FZ7AACMr4bWzphq4+jeumZcx0K+7+vJ8j3lPAAAYDIwQxAAAAAAEhEEAQAAACARS4aBabUsdTKxNBAAAIDJyAxBAAAAAEhEEAQAAACARCwZBpgELLnOZ6peJZeJ420HAAAYL2YIAgAAAEAigiAAAAAAJGLJMACpWJ6dk+W3MDl4uwSmCq8bwHRnhiAAAAAAJCIIAgAAAEAilgwDMOVNlmXAk2UcU/X3aMkVwNixPBuAczFDEAAAAAASEQQBAAAAIBFLhgFgCnC1w8kpwzJxAKrH0m/Gku8n/pMZggAAAACQiCAIAAAAAIlYMgwAyVn2ejpfj9NZXpSPP3OmK3+/A/w/ZggCAAAAQCKCIAAAAAAkYskwAEwzlkTB+cmwRNbfC/n+zCfL18/XDmByMkMQAAAAABIRBAEAAAAgEUuGAYBJwZLGfF9ryw6ZKnyvAjDdmCEIAAAAAIkIggAAAACQiCXDAAAwCUyWpdyTyVRcqjtVr2Ds+296fK3H65wZz+/rDOfMeI55Kn4/MTmYIQgAAAAAiQiCAAAAAJCIJcMATDqWLQHA9DBVl4Nm+HfLZFlqOp6fe7J8P03V75HJ8nucLH+O040ZggAAAACQiCAIAAAAAInUVCqVSkwydXV10dvbG9NVhunCAADkMJ5XE81gvJbC+VrD+J6LzrHpoXuaL0c+V18zQxAAAAAAEhEEAQAAACARVxkGAABGzLK50fH1A6AazBAEAAAAgEQEQQAAAABIZNyXDHd1dcW9994br776alx00UXxzW9+M9797neP92EBAAAAhsXyfbIZ9xmCGzZsiObm5njppZdi8+bNsX79+vE+JAAAAABQjSA4MDAQ+/fvj7vvvrt8fMcdd8TRo0fj0KFD43lYAAAAAKAaS4aL+Ld48eKorf33YWpqaqK+vj56enpi+fLlQ89ra2srb6f09/dHXV1dTFeDg4MxZ86cag8DUnMeQvU5D6G6nINQfc5DqK66jul9Hv7xj3+s3nsIDkdLS0t5y6KInb29vdUeBqTmPITqcx5CdTkHofqch1B9dUnPw3FdMrx06dLo6+uLkydPlo8rlUo5O7CYJQgAAAAATLMguGDBglixYkV0dHSUj3fu3FmW1/9cLgwAAAAATJxxXzL8yCOPlFcW3rJlS8ybNy/a29sju0zLo2Gych5C9TkPobqcg1B9zkOovpak52FNpVjHCwAAAACkMK5LhgEAAACAyUUQBAAAAIBEBEEAAAAASEQQnGBdXV1xww03xGWXXRZNTU3x4osvVntIMOVt2rQpGhoaoqamJg4cODCs822k+4Azvf7663H77beX58zVV18d73//++PQoUPlvoGBgbj11lujsbExrrjiitizZ8/Qx410H3B2H/jAB+Kqq66Ka665Jm666ab45S9/WW73eggTq7iQZvHv0scff7x87LUQJk7xc+Hll19evhYWt+985zvldq+FZ1FcVISJc/PNN1fa29vL+9/97ncr119/fbWHBFPe7t27K0ePHq0sW7as8stf/nJY59tI9wFn+vvf/17p7OysvPHGG+Xjhx9+uLJ69ery/ic/+cnKF77whfL+z3/+88rb3va2yj//+c9R7QPO7s9//vPQ/V27dlWuuuqq8r7XQ5g4R44cqbz3ve+trFy5svL973+/3Oa1ECbO//8z4SleC88kCE6gV155pTJ37tzKiRMnysfFD04LFy6sdHV1VXtoMO3+8j/X+TbSfcDw7Nu3rzwfC29+85srfX19Q/uampoqTz311Kj2Af9b8cPL1Vdf7fUQJtC//vWvyi233FLZv39/+R9jp4Kg10KobhD0Wnh2tWebNcj4OHr0aCxevDhqa//9ZS+mkdfX10dPT08sX7682sODNOfbRRddNKJ9zlMYnoceeihuu+22OH78eJw4cSIWLVp02jKO4nwa6T7g3O655574yU9+Ut7/wQ9+4PUQJlBbW1vceOONcd111w1t81oI1XktLCbAvec974mtW7d6LfwvvIcgADBmtmzZUr5/4Je//OVqDwVS+va3v13+4POlL30pNm/eXO3hQBovvPBC7Ny5Mz73uc9VeyiQWvFem7/+9a/jF7/4RVxyySVx7733VntIk5YgOIGWLl0afX19cfLkyfJxUayLslwUZmDizreR7gPO7cEHH4xdu3bFE088ERdeeGHMnz+//B/V/v7+oed0d3eX59NI9wHDU/wAVMwUrKur83oIE+DZZ58tX6uKC4AUM/mee+65aG5ujh07dngthAl06hyZOXNmfPazny3PTT8bnp0gOIEWLFgQK1asiI6OjvJx8T9IxT/SpsNUU5hK59tI9wHnXib12GOPxVNPPRUXX3zx0Pa1a9fG9u3by/v79u2LY8eOxerVq0e1DzjTX/7yl/jDH/4w9Li4umkRFLwewsS4//77y3BQRLvitnLlynj00UfL7V4LYWK89tpr5evhKcW/Ta+99lqvhf9FTfFGgv9tJ2Pv4MGDsX79+vI9IebNm1dekv7KK6+s9rBgStuwYUN0dnaW/4Na/PAzd+7ccsniuc63ke4DztTb21v+D+qll15ann+F2bNnx/PPPx+vvPJKrFu3Lo4cORKzZs2Kr371q3HzzTeXzxnpPuBML7/8chkP/v73v8eMGTPirW99azlr95prrvF6CFXwvve9r5yddPvtt3sthAny+9//Pu64447417/+Vc7mK/5tWry3dTFr12vhmQRBAAAAAEjEkmEAAAAASEQQBAAAAIBEBEEAAAAASEQQBAAAAIBEBEEAAAAASEQQBAAAAIBEBEEAAAAASEQQBAAAAIDI4/8AKY0kd/jNUaEAAAAASUVORK5CYII="
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "execution_count": 3
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
